A new index for the intensity of natural selection.

A new index for the intensity of natural selection is proposed, based upon the double exponential model for fitness functions. This index is defined as a variance and is such that a value of zero indicates no selection while a value of one indicates quite strong selection. The use of the index is demonstrated using published data on the survival of human infants with different birth weights and gestation times.     

Note on a method for analyzing stage-frequency data

A new method for analyzing stage-frequency data is proposed which is based on the estimation of rates of transition between one stage and the next highest stage in one unit of time, and a unit time survival rate that is assumed to be constant. Once these estimates are calculated it becomes possible to also estimate the mean durations of stages, stage-specific survival rates, and numbers entering stages. An advantage of the method is that it can be applied with any distribution of entry times to stage 1, and any distribution of numbers in stages when sampling begins. Use of the method is illustrated on data from a copepod population in a Canadian lake.     

A method for the estimation of parameters for natural stage-structured populations

A relatively simple method is proposed for the estimation of parameters of stage-structured populations from sample data for situation where (a) unit time survival rates may vary with time, and (b) the distribution of entry times to stage 1 is too complicated to be fitted with a simple parametric model such as a normal or gamma distribution. The key aspects of this model are that the entry time distribution is approximated by an exponential function withp parameters, the unit time survival rates in stages are approximated by anr parameter exponential polynomial in the stage number, and the durations of stages are assumed to be the same for all individuals. The new method is applied to four Zooplankton data sets, with parametric bootstrapping used to assess the bias and variation in estimates. It is concluded that good estimates of demographic parameters from stagefrequency data from natural populations will usually only be possible if extra information such as the durations of stages is known.     

The influence of environmental variables on capybara (Hydrochoerus hydrochaeris: Rodentia, Hydrochoeridae) detectability in anthropogenic environments of southeastern Brazil

Capybaras were monitored weekly from 1998 to 2006 by counting individuals in three anthropogenic environments (mixed agricultural fields, forest and open areas) of southeastern Brazil in order to examine the possible influence of environmental variables (temperature, humidity, wind speed, precipitation and global radiation) on the detectability of this species. There was consistent seasonality in the number of capybaras in the study area, with a specific seasonal pattern in each area. Log-linear models were fitted to the sample counts of adult capybaras separately for each sampled area, with an allowance for monthly effects, time trends and the effects of environmental variables. Log-linear models containing effects for the months of the year and a quartic time trend were highly significant. The effects of environmental variables on sample counts were different in each type of environment. As environmental variables affect capybara detectability, they should be considered in future species survey/monitoring programs.     

<Emphasis Type="Italic">mab-31</Emphasis> and the TGF-β pathway act in the ray lineage to pattern <Emphasis Type="Italic">C. elegans</Emphasis>male sensory rays

Background  

C. elegans TGF-β-like Sma/Mab signaling pathway regulates both body size and sensory ray patterning. Most of the components in this pathway were initially identified by genetic screens based on the small body phenotype, and many of these mutants display sensory ray patterning defect. At the cellular level, little is known about how and where these components work although ray structural cell has been implicated as one of the targets. Based on the specific ray patterning abnormality, we aim to identify by RNAi approach additional components that function specifically in the ray lineage to elucidate the regulatory role of TGF-β signaling in ray differentiation.     

Constraints on body size distributions: an experimental approach using a small-scale system

Holling’s (1992) proposition that discontinuities in biotic and abiotic processes generate structure in ecological systems is examined experimentally by imposing size-specific perturbations on marine sediment assemblages. Two kinds of perturbations were applied: organic enrichment and predation, each at two levels. Perturbations significantly affected the densities and relative abundance of the main invertebrate taxa and these effects were consistent with the known effects of enrichment and predation. However, there was little evidence of significant treatment effects on the overall benthic biomass or abundance size spectrum, supporting the contention that the spectrum is conservative and is probably constrained by habitat architecture. Received: 28 June 1999 / Accepted: 24 September 1999     

A Genetic Linkage Map of the Mouse Using Restriction Landmark Genomic Scanning (Rlgs)

We have developed a multiplex method of genome analysis, restriction landmark genomic scanning (RLGS) that has been used to construct genetic maps in mice. Restriction landmarks are end-labeled restriction fragments of genomic DNA that are separated by using high resolution, two-dimensional gel electrophoresis identifying as many as two thousand landmark loci in a single gel. Variation for several hundred of these loci has been identified between laboratory strains and between these strains and Mus spretus. The segregation of more than 1100 RLGS loci has been analyxed in recombinant inbred (RI) strains and in two separate interspecific genetic crosses. Genetic maps have been derived that link 1045 RLGS loci to reference loci on all of the autosomes and the X chromosome of the mouse genome. The RLGS method can be applied to genome analysis in many different organisms to identify genomic loci because it used end-labeling of restriction landmarks rather than probe hybridization. Different combinations of restriction enzymes yield different sets of RLGS loci providing expanded power for genetic mapping.